The productive operation of industrial machinery requires machines to be in good working order. Methods of machine condition monitoring have been developed to detect component defects before catastrophic failure. One method is a spectral analysis of the vibration produce by the machine. Faults such as shaft imbalance, misalignment, looseness, bearing faults (such as cage, roller, and race faults), and gear faults produce characteristic fault signatures. These signatures include a set of specific spectral vibration frequencies. Often, the fault signature is a set of frequencies proportional to the rotation rate of the shafts in the machine. Knowing the rotation speed of each shaft and the physical properties of the component allows the calculation of fault frequencies associated with a specific type of fault for a particular component. For example, a bearing outer race will produce a harmonic set of frequencies with a fundamental frequency at the rolling element outer race pass frequency. Once calculated, these frequencies can be monitored to aid in detecting mechanical faults in the equipment.
Commercial vibration monitoring systems are available that track the spectral amplitudes in a narrow frequency band around these expected frequencies. A narrow band is used rather than the exact fault frequency because the rotation speed may not be known precisely and because components, such as bearings, for example, can slip slightly causing the fault to appear at a slightly different frequency than the theoretically calculated fault value. The bandwidth of fault frequencies is chosen to be greater than the signature frequency deviation expected due to rotation speed inaccuracies and possible slippage. One fault measure, the spectral amplitude sum, Sb, is the sum of all spectral amplitudes falling within the narrow frequency bands around each theoretical fault frequency associated with the component fault. This spectral amplitude sum is interpreted as a measure of the severity of a specific component fault.
This method is inadequate in many cases as it suffers from several problems. For example, there can be interfering vibration sources that happen to produce a vibration frequency which falls into one of the frequency band regions. This interfering vibration source will contribute to the spectral amplitude sum, but it is not associated with the actual fault of interest. For example, a gear mesh frequency may fall in one of the harmonic bands of a bearing fault. Another problem with this spectral amplitude sum technique is that spectral background amplitudes may rise, thereby increasing the sum of all spectral amplitudes falling within the frequency bands around the theoretical fault frequencies. This would mistakenly be interpreted as an increase in the fault severity. These problems can lead to false alarms as to the presence of a component fault. Additionally, an incorrectly established threshold can also lead to a false alarm or a false pass condition.
A mechanical fault detection and analysis system should be flexible and accurate. Different approaches have been used in the past to provide adaptable and responsive techniques that are free from errors.